In today’s digital world, a successful online business goes beyond presenting users with a vast array of options. This is especially true for Imobiliare.ro, the leading real estate (property) portal on the Romanian market, with more than 100.000 property listings and over 1.6 million monthly unique visitors.
The topics covered in the case study:
Which Machine Learning techniques enable you to provide recommendations tailored to your user’s explicit and implicit preferences?
Across which dimensions do recommendations perform best?
Which technology stacks are required to deploy a multichannel online recommendation engine?
"The Online Recommendation Engine led to an increase in user leads due to the improvements in our conversion rates. A/B testing recorded outstanding performance in key metrics: +59% user clicks and +81% leads."
Ciprian Gheran, Managing Partner & Product Owner Imobiliare.ro